"""Handler for automation and orchestration operations."""

from datetime import datetime, timedelta
from typing import Any
import hashlib

from ludus_mcp.core.client import LudusAPIClient
from ludus_mcp.utils.logging import get_logger

logger = get_logger(__name__)


class AutomationOrchestrationHandler:
    """Handler for automation and orchestration."""

    def __init__(self, client: LudusAPIClient) -> None:
        """Initialize the automation orchestration handler."""
        self.client = client

    async def create_deployment_pipeline(
        self,
        pipeline_name: str,
        stages: list[dict],
        user_id: str | None = None
    ) -> dict[str, Any]:
        """Define multi-stage deployment pipelines."""
        try:
            pipeline_id = hashlib.md5(f"{pipeline_name}{datetime.now()}".encode()).hexdigest()[:8]

            # Validate stages
            for i, stage in enumerate(stages):
                if "name" not in stage:
                    return {"status": "error", "error": f"Stage {i} missing 'name' field"}
                if "action" not in stage:
                    return {"status": "error", "error": f"Stage {i} missing 'action' field"}

            pipeline = {
                "pipeline_id": pipeline_id,
                "name": pipeline_name,
                "created_at": datetime.now().isoformat(),
                "stages": stages,
                "total_stages": len(stages)
            }

            return {
                "status": "success",
                "timestamp": datetime.now().isoformat(),
                "pipeline": pipeline,
                "execution_guide": {
                    "manual": "Execute each stage using corresponding ludus tools",
                    "automated": "Use CI/CD platform (GitHub Actions, GitLab CI) to orchestrate",
                    "example": "Stage 1: ludus.update_range_config -> Stage 2: ludus.deploy_range -> Stage 3: ludus.start_testing"
                }
            }
        except Exception as e:
            logger.error(f"Error creating deployment pipeline: {e}")
            return {"status": "error", "error": str(e)}

    async def schedule_range_tasks(
        self,
        task_type: str,
        schedule: str,
        parameters: dict | None = None,
        user_id: str | None = None
    ) -> dict[str, Any]:
        """Schedule recurring tasks (start/stop, snapshots)."""
        try:
            valid_tasks = ["power_on", "power_off", "snapshot", "health_check"]
            if task_type not in valid_tasks:
                return {
                    "status": "error",
                    "error": f"Invalid task_type. Must be one of: {valid_tasks}"
                }

            # Validate cron schedule
            schedule_parts = schedule.split()
            if len(schedule_parts) != 5:
                return {
                    "status": "error",
                    "error": "Invalid cron schedule format. Expected: 'minute hour day month weekday'"
                }

            task_id = hashlib.md5(f"{task_type}{schedule}{datetime.now()}".encode()).hexdigest()[:8]

            task_config = {
                "task_id": task_id,
                "task_type": task_type,
                "schedule": schedule,
                "parameters": parameters or {},
                "created_at": datetime.now().isoformat(),
                "enabled": True,
                "next_run": self._estimate_next_run(schedule)
            }

            return {
                "status": "success",
                "timestamp": datetime.now().isoformat(),
                "task_configuration": task_config,
                "implementation": {
                    "crontab": f"{schedule} ludus-fastmcp-task {task_type}",
                    "systemd_timer": "Create systemd timer unit",
                    "k8s_cronjob": "Deploy as Kubernetes CronJob"
                }
            }
        except Exception as e:
            logger.error(f"Error scheduling range task: {e}")
            return {"status": "error", "error": str(e)}

    async def auto_scaling(
        self,
        rules: list[dict],
        user_id: str | None = None
    ) -> dict[str, Any]:
        """Define auto-scaling rules based on resource usage."""
        try:
            # Validate rules
            for i, rule in enumerate(rules):
                required_fields = ["metric", "threshold", "action"]
                for field in required_fields:
                    if field not in rule:
                        return {
                            "status": "error",
                            "error": f"Rule {i} missing required field: {field}"
                        }

            scaling_config = {
                "enabled": True,
                "rules": rules,
                "created_at": datetime.now().isoformat(),
                "monitoring_interval_seconds": 60
            }

            return {
                "status": "success",
                "timestamp": datetime.now().isoformat(),
                "scaling_configuration": scaling_config,
                "note": "Auto-scaling requires external monitoring and orchestration system",
                "implementation_guide": {
                    "metrics_collection": "Use ludus.get_range_metrics periodically",
                    "decision_engine": "Compare metrics against thresholds",
                    "actions": "Execute ludus.update_range_config to adjust resources"
                },
                "example_rule": {
                    "metric": "cpu_utilization",
                    "threshold": 80,
                    "comparison": "greater_than",
                    "action": "increase_cpus",
                    "action_parameters": {"increment": 1}
                }
            }
        except Exception as e:
            logger.error(f"Error configuring auto-scaling: {e}")
            return {"status": "error", "error": str(e)}

    async def health_checks(
        self,
        check_interval_minutes: int = 5,
        alert_on_failure: bool = True,
        user_id: str | None = None
    ) -> dict[str, Any]:
        """Automated health checks with alerting."""
        try:
            range_info = await self.client.get_range(user_id)

            health_check_config = {
                "enabled": True,
                "interval_minutes": check_interval_minutes,
                "alert_on_failure": alert_on_failure,
                "checks": [
                    {
                        "name": "range_state",
                        "description": "Check if range is in SUCCESS state",
                        "endpoint": "ludus.get_range",
                        "expected": "rangeState == SUCCESS"
                    },
                    {
                        "name": "vm_health",
                        "description": "Check if all VMs are running",
                        "endpoint": "ludus.get_range",
                        "expected": "all VMs have status == running"
                    },
                    {
                        "name": "deployment_logs",
                        "description": "Check for errors in logs",
                        "endpoint": "ludus.get_range_logs",
                        "expected": "no ERROR or FAILED messages"
                    }
                ],
                "alert_channels": {
                    "email": "Configure SMTP settings",
                    "slack": "Use ludus.slack_notifications",
                    "webhook": "Use ludus.webhook_integration"
                }
            }

            # Perform initial health check
            vms = range_info.get("VMs", [])
            running_vms = sum(1 for vm in vms if vm.get("status") == "running")
            health_status = "healthy" if running_vms == len(vms) else "degraded"

            return {
                "status": "success",
                "timestamp": datetime.now().isoformat(),
                "health_check_configuration": health_check_config,
                "current_health": {
                    "status": health_status,
                    "range_state": range_info.get("rangeState"),
                    "vms_running": f"{running_vms}/{len(vms)}"
                },
                "implementation": {
                    "polling": "Use cron or systemd timer to run checks",
                    "monitoring": "Integrate with Prometheus/Grafana for visualization"
                }
            }
        except Exception as e:
            logger.error(f"Error configuring health checks: {e}")
            return {"status": "error", "error": str(e)}

    def _estimate_next_run(self, schedule: str) -> str:
        """Estimate next run time (simplified)."""
        # In production, use croniter library
        return f"Estimated based on schedule: {schedule}"
